Introduction to Machine Learning Series

This workshop series is designed to provide participants with a foundational understanding of the concepts, techniques, and tools used in machine learning. Through a combination of lectures and iteractive exercises, participants will gain practical experience with some of the most popular machine-learning algorithms and techniques.

The workshop series will cover a range of topics including supervised and unsupervised learning and introduces the most popular machine learning algorithms and techniques such as regression, clustering, and neural networks. In addition to learning about the technical aspects of machine learning, this workshop also aims to promote critical thinking about the ethical implications of machine learning. Participants will examine the potential impact of machine learning on society and explore ethical considerations related to data privacy, bias, and fairness.

By the end of the workshop series, participants will have a broad understanding of the concepts and techniques used in machine learning, as well as some familiarity with the ethical considerations that underlie this field. This workshop series is suitable for anyone who is interested in learning about machine learning, regardless of their technical background or prior experience.

Structure

Note: For interactive part of the workshop, we will run some Python codes on Jupyter Notebooks. You don’t need to have Python installed. Please make sure that you have a Google Colaboratory account.

Workshop 1: Introduction & Regression Model

Workshop 2: Classification & Clustering

Workshop 3: Neural Network

This workshop involves the use of programming tools and libraries commonly employed in machine learning projects, such as Python and scikit-learn. As such, prior familiarity with Python programming is recommended for participants to fully benefit from the practical component of the workshop.

** Disclosure**: The workshop description and course plan is partially prepared using ChatGPT.

Learning objectives

At the end of this workshop series, you will be able to:

Define Machine Learning and recall the types of Machine Learning
Compare methods and techniques of Machine Learning
Identify appropriate methods based on the use cases
Think about the ethical implications of using Machine Learning

Slides

Find the first workshop slides below or open it in a new tab: